Diabetes mellitus is a disorder in which the pancreas cannot create sufficient insulin (Type I or insulin dependent) and/or in which insulin is not effective (Type 2 or non-insulin dependent). In the diabetic state, the victim suffers from high blood sugar, which causes an array of physiological derangements (kidney failure, skin ulcers, or bleeding into the vitreous of the eye) associated with the deterioration of small blood vessels. A hypoglycemic reaction (low blood sugar) may be induced by an inadvertent overdose of insulin, or after a normal dose of insulin or glucose-lowering agent accompanied by extraordinary exercise or insufficient food intake.
Conventionally, a diabetic person carries a self-monitoring blood glucose (SMBG) monitor, which typically requires uncomfortable finger pricking methods. Due to the lack of comfort and convenience, a diabetic will normally only measure his or her glucose level two to four times per day. Unfortunately, these time intervals are spread so far apart that the diabetic will likely find out too late, sometimes incurring dangerous side effects, of a hyperglycemic or hypoglycemic condition. In fact, it is not only unlikely that a diabetic will take a timely SMBG value, but additionally the diabetic will not know if his blood glucose value is going up (higher) or down (lower) based on conventional methods.
Consequently, a variety of non-invasive, transdermal (e.g., transcutaneous) and/or implantable electrochemical sensors are being developed for continuously detecting and/or quantifying blood glucose values. These devices generally transmit raw or minimally processed data for subsequent analysis by the device or at a remote device, which can include a display.
Conventional processing of the raw data by a device are generally directed towards displaying information to the users regarding their recent glucose trend and helping them take short term actions, which in turn helps them stay in the target range and improves the average glucose over a period of time. Patients may also review data downloads either on their own or with their health care physician to decide on longer term behavioral changes.
However, some issues with conventional tools for analyzing data exist. Among these issues are the amount of time required to analyze the data and the lack of user participation in downloading or analyzing the data. For example, reviewing the downloads using trend graphs is time consuming and requires some amount of expertise to detect problem areas. Additionally, many users do not consider reviewing downloads, or even initiating downloads from the receivers, and are often unaware of some issues that may exist. Finally, conventional techniques may provide excessive alerts to the user, including alerts in response to measurements that do not pose a risk to the user. As a result, the user may ignore some important alerts which are provided by the conventional systems to their detriment.